Cell and evolved node B station outage restoration tool

ABSTRACT

During scheduled or unscheduled wireless communication outage, restoration of crucial or critical cell site devices and/or base station device are prioritized. The system filters current key performance indicator values and historical key performance indicator values for a reference cell device to produce a filtered key performance indicator metric for the reference cell device, filters statistical data to produce filtered statistical data representing a filtered statistic for the reference cell device, determines a weighting factor for the reference cell device, and displays of a ranking score determined as a function of the weighting factor, the filtered statistic data, and the filtered key performance indicator metric. The ranking score provides an ordering that can be used to restore critical cell site devices and/or base station devices.

TECHNICAL FIELD

The disclosed subject matter relates to a real time self healing cellsite and evolved Node B (eNodeB) station device outage restoration toolapplicable, for example, in self organizing networks.

BACKGROUND

When disruptive and/or operational multiple access wirelesscommunication network outage problems occur, for example, due to naturaldisasters, scheduled and/or unscheduled outages, and/or other unforeseencircumstances, restoration of cell sites, and/or eNodeB stations devicesthat can control respective cell sites, in an orderly fashion can be ofparamount importance given the current preference of many in thepopulace to exclusively employ the functionalities and facilitiesprovided by multiple access wireless communicationnetworks/infrastructures.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is an illustration of a system for restoring cell sites and/oreNodeB station devices after a scheduled and/or unscheduled wirelesscommunication outage in accordance with aspects of the subjectdisclosure.

FIG. 2 is a further depiction of a system for restoring cell sitesand/or eNodeB station devices after a scheduled and/or unscheduledwireless communication outage in accordance with aspects of the subjectdisclosure.

FIG. 3 illustrates a further system for restoring cell sites and/oreNodeB station devices after a scheduled and/or unscheduled wirelesscommunication outage in accordance with aspects of the subjectdisclosure.

FIG. 4 is still yet a further illustration of a system for restoringcell sites and/or eNodeB station devices after a scheduled and/orunscheduled wireless communication outage in accordance with aspects ofthe subject disclosure.

FIG. 5 depicts a wireless cellular structure comprising a reference cellsite proximate or neighboring cell sites in accordance with aspects ofthe subject disclosure.

FIG. 6 provides illustration of a histogram representative of a numberof wireless handovers that have occurred between a reference cell siteand each cell site that is proximate or neighbors the reference cellsite in accordance with aspects of the subject disclosure.

FIG. 7 provides illustration of a set of contiguous cell sites inaccordance with aspects of the subject disclosure.

FIG. 8 illustrates a method for restoring cell sites and/or eNodeBstation devices after a scheduled and/or unscheduled wirelesscommunication outage in accordance with aspects of the subjectdisclosure.

FIG. 9 illustrates a further method for restoring cell sites and/oreNodeB station devices after a scheduled and/or unscheduled wirelesscommunication outage in accordance with aspects of the subjectdisclosure.

FIG. 10 is a block diagram of an example embodiment of a mobile networkplatform to implement and exploit various features or aspects of thesubject disclosure.

FIG. 11 illustrates a block diagram of a computing system operable toexecute the disclosed systems and methods in accordance with anembodiment.

DETAILED DESCRIPTION

The subject disclosure is now described with reference to the drawings,wherein like reference numerals are used to refer to like elementsthroughout. In the following description, for purposes of explanation,numerous specific details are set forth in order to provide a thoroughunderstanding of the subject disclosure. It may be evident, however,that the subject disclosure may be practiced without these specificdetails. In other instances, well-known structures and devices are shownin block diagram form in order to facilitate describing the subjectdisclosure.

When there is a natural disaster or other operational outage there is aneed to prioritize which cell sites and/or eNodeB station devices shouldbe remediated first. Currently, there is no mechanism to identify thekey sites (e.g. sites that when revived that would yield the greatestpossible benefit to the overall functionality of the multiple accesswireless communication network/infrastructure and/or a geographical areaparticularly or specifically affected by the natural disaster or otheroperational challenges) necessary to bring the multiple access wirelesscommunication network/infrastructure (or a geographic portion thereof)back to full functionality.

Currently there is no tool that prioritizes or highlights cell sites,sets or groups of cell sites and/or sets or groups of eNodeB stationdevices, that should be brought online in preference to other sets orgroups of cells sites and/or other sets or groups of eNodeB stationdevices. It should be noted in this regard, that for the purposes of thesubject disclosure, that a set or group of cell sites and/or sets orgroups of eNodeB station devices is not inclusive of an empty set or anull set.

In order to remedy the foregoing and current omission, the subjectdisclosure provides systems and/or method that rank orders cell sitesand/or eNodeB station devices that should be brought back or restored inorder of greatest import and impact to the functionality of the multipleaccess wireless communication network/infrastructure. The subjectdisclosure rank orders cell sites and/or eNodeB station devices as afunction of the order in which each cell site and/or eNodeB stationdevice should be restored or brought back online, thereby ensuringdisruptions to the multiple access wireless communicationnetworks/infrastructure are obviated or at the very least mitigatedand/or minimized.

In order to achieve and/or facilitate this aim, the subject applicationuses historical data from each cell site and/or eNodeB station device toprovide a relative ranking of importance of the cell site and/or eNodeBstation device to the overall facility and/or functioning of themultiple access wireless communication network/infrastructure (or ageographical portion thereof) that can have suffered a deficiency due toa scheduled or unscheduled network outage or due to a natural disasteror other unscheduled disruption.

The functionality provided by the subject disclosure is performed inreal-time rather than over an extended period of time. The multipleaccess wireless communication network/infrastructure can be viewed orperceived as a dynamic and mutable entity; an entity that is in aperpetual state of flux. For instance, certain aspects of ageographically diverse multiple access wireless communication networkcan be subject to scheduled and/or unscheduled outages, such that thecomposition and functionality of the geographically diverse anddisparate multiple access wireless communication network/infrastructurecan change from one instance of time to another instance of time, andwherein the likelihood that the entirety of the multiple access wirelesscommunication networks/infrastructure will remain statically andidentically configured over time is extremely remote. The subjectdisclosure therefore provides its results in real time and as a functionof the alterable and/or persistently mutable nature of multiple accesswireless communication networks/infrastructures.

The subject application takes as input current and historical keyperformance indicators (KPIs) values (e.g., voice erlangs, data traffic,short message service (SMS) traffic, carried and/or offered loads on thecell site), network topology, and cell site relation information, suchas those based on handover (HO) statistics. The time window andgranularity over which information is collected and processed can bevariable and can be set by the multiple access wireless communicationnetwork/infrastructure provider/operator.

The key performance indicator values, employed in the subjectdisclosure, can first be filtered using a generic filteringalgorithm/process, such as, simple moving average, cumulative movingaverage, weighted moving average, exponential weighted moving average,and the like, which can combine current and historical key performanceindicator information within a specified time window to produce a postprocessed value for the key performance indicator metric that can bedenoted as (Filtered_KPI)_(j) for each reference cell site j.

The next factor that the subject disclosure can consider is handoverstatistics, the total number of handovers that can have occurred in adefined time window between a reference cell site j and each of itsneighbors, is filtered and weighted using the same or a similarfiltering algorithm/process as utilized in the context of keyperformance indicator values. The post processed handover metric for aparticular reference cell site j can be denoted as (Filtered_HO)_(j).

A further factor that can be considered by the subject disclosure can bebased on using the network topology, wherein a distance weighting factorcan be constructed that weights the contributions from neighboring cellsites based on the distance between the reference cell site j and eachof its neighbors. This metric can be determined as follows: first, usingthe network topology information obtained for example from a database ornetwork topologies typically maintained by a multiple access wirelesscommunication network provider/carrier, a distance between a referencecell site j and each of its neighboring cell sites defined in thenetwork topology can be determined. This set of distances can be denotedas D_(net) _(—) _(top). Next, using the handover statistics, alsomaintained in one or more databases typically maintained by the multipleaccess wireless communication network provider/carrier, the number ofneighbor cell sites that have contributed to a percentage value (x %) ofthe total handovers that have occurred during a defined period of timecan be identified. Based on, or as a function of, the handoverstatistics and the set of distances between reference cell site j andeach of its neighboring cell sites, a respective distance from referencecell site j and to each of the neighbor cell sites that have contributedto a percentage value (x %) of the total handovers can be determined.This set of distances can be denoted as D_(HO) _(—) _(stat). Using theset of distances D_(HO) _(—) _(stat), a weighting function for thereference cell site j can be constructed. This weighting function can bedenoted as W_(j) which measures the cardinality (e.g., a measure of the“number of elements included in the set”) of the set of distances D_(HO)_(—) _(stat).

Based on the foregoing, a cell site ranking score value for a referencecell site j can be constructed as:Cell_Ranking_Score_(j)=(Filtered_KPI_(j)+Filtered_HO_(j))×W_(j).Further, using the foregoing cell site ranking score(Cell_Ranking_Score), an eNodeB station device ranking score can bedetermined for a reference eNodeB station device j using the formula:eNodeB_Ranking_Score_(j)=Σ_(i=1) ^(N) ^(i) Cell_Ranking_Score_(i), whereN_(i) is the number of cell sites controlled by reference eNodeB stationdevice j.

As has been noted earlier, the foregoing determinations and/orCell_Ranking_Score and/or eNodeB_Ranking_Score can be performed in realtime, consequently it will be appreciated by those of ordinary skillthat the subject application can produce results in real time. Thesubject disclosure as described and disclosed herein, thereforeefficiently and in real time provides a cell site and/or eNodeB stationdevice restoration priority ranking metric; the defined metric accountsfor all the relevant key performance indicator factors and assigns anoptimal weight to each cell site and/or to each eNodeB station device toreflect its relative importance and priority for restoration duringoutage and disaster recovery scenarios. Accordingly, the system andmethods disclosed and described herein can reduce the cost of restoringand troubleshooting wireless networks through the provision of real-timemetrics that can aid a network operator to efficiently and quicklyidentify and repair cell sites and/or eNodeB station devices duringoutage scenarios. This minimizes the time to restore cell sites and/oreNodeB station devices, and hence to provide wireless coverage tocritical areas and improved customer experience.

In accordance with an embodiment, the subject disclosure describes asystem comprising a memory to store executable instructions, and aprocessor, coupled to the memory, that facilitates execution of theexecutable instructions to perform operations. The operations caninclude receiving, from the memory, a local database, and/or a remotelylocated database, a current key performance indicator value, topologydata representing a geographically relevant network topology (e.g., anetwork topology within which at least a first cell device cell deviceis located), and statistical data representing a statistic related to anumber of transfers of wireless service from a first cell device to asecond cell device, wherein the current key performance indicator valueis a measure of a current load on the first cell device and/or thecurrent key performance indicator value is a metric related to a numberof simultaneous/concurrent voice calls that are being service by thefirst cell device in (or during) the defined time period. Furtheroperations performed by the system can include filtering the currentperformance indicator value for the first cell device over a definedtime period to produce a filtered key performance indicator metric forthe first cell device, filtering the statistical data over the definedtime period to produce filtered statistical data representing a filteredstatistic for the first cell device of the number of transfers ofwireless service from the first cell device to the second cell device,determining, as a function of the topology data, a weighting factor forthe first cell device based on distance data representing a distancebetween the first cell device and the second cell device and the numberof transfers of wireless service from the first cell device to thesecond cell device; and initiating display of a cell ranking score forthe first cell device as a function of the weighting factor for thefirst cell device, the filtered key performance indicator metric for thefirst cell device, and the filtered statistical data for the first celldevice.

Additional operations that can be performed by the system can alsoinclude receiving, from the memory, a local storage device, and/or aremotely situated database, a historical key performance indicator valueand filtering the historical performance indicator value for the firstcell device and the current key performance indicator value for thefirst cell device over the defined time period to produce the filteredkey performance indicator for the first cell device, aggregating thecell ranking score for cell devices included in a coverage area of abase station device to produce a base station device ranking score forthe base station device, and initiating display of the base stationdevice ranking score, wherein the first cell device and the second celldevice are included in the coverage area of the base station device, andthe base station device is included in the topology data.

In accordance with a further embodiment, the subject disclosuredescribes a method, comprising a series of acts that include obtaining,by a system comprising a processor, a historical key performanceindicator value, topology data representing a network topology, andstatistical data representing a metric related to a number of transfersof wireless service from a reference cell device to a neighbor celldevice; applying a filtering process to the historical performanceindicator value for the reference cell device to produce a filtered keyperformance indicator metric for the reference cell device; applying thefiltering process to the statistical data for the reference cell deviceto produce a filtered handover metric related to the number of transfersof wireless service from the reference cell device to the neighbor celldevice; determining a weighting factor for the reference cell deviceusing the topology data and the number of transfers of wireless servicefrom the reference cell device to the neighbor cell device, wherein thetopology data provides, or enables determination of, a distance betweenthe reference cell device and the neighbor cell device; and initiatingdisplay of a cell ranking score for the reference cell device as afunction of the weighting factor for the reference cell device, thefiltered handover metric for the reference cell device, and the filteredkey performance indicator metric for the reference cell device.

In the context of the filtering process a weighted moving averageprocess or algorithm and/or an exponential weighted moving averageprocess or algorithm can be used. Further, in the context of thehistorical key performance value, in accordance with an embodiment, thehistorical key performance indicator value can be a metric related to aquantity of data traffic passing through the reference cell device in adefined unit of time. Additionally, in accordance with a furtherembodiment, the historical key performance indicator value can be ametric related to an amount of data related to a text message serviceusing the reference cell device as a conduit for communication with anetwork device associated with a multiple access wireless communicationnetwork.

Additional acts that can also include aggregating the cell ranking scorefor the reference cell device with a cell ranking score determined forthe neighbor cell device to determine an eNodeB station device rankingscore for a reference eNodeB station device, wherein the referenceeNodeB station device includes or comprises the reference cell device,and initiating display of the eNodeB station device ranking score forthe reference eNodeB station device, wherein the eNodeB station rankingscore is color coded as a function of a priority ordering placed onrestoration of the reference eNodeB station device relative to theneighbor cell device included in a geographic segment of a multipleaccess wireless communication network represented by the topology data.

In accordance with a still further embodiment, the subject disclosuredescribes a computer readable storage device comprising instructionsthat, in response to execution, cause a computing system comprising aprocessor to perform operations. The operation can include filtering acurrent key performance indicator value for a reference cell device anda historical key performance indicator value for the reference celldevice to produce a filtered key performance indicator metric for thereference cell device related to a defined time horizon, filteringstatistical data to produce filtered statistical data representing afiltered statistic for the reference cell device related to the definedtime horizon, determining a weighting factor for the reference celldevice as a function a distance between the reference cell device and acell device in proximity to the reference cell device, wherein thedistance is obtained from topology data representing a network topologythat includes or comprises the reference cell device and the cell devicein proximity to the reference cell device, and initiating display of aranking score for the reference cell device, wherein the ranking scorefor the reference cell device is determined as a function of theweighting factor for the reference cell device, the filtered statisticaldata for the reference cell device, and the filtered key performanceindicator metric for the reference cell device.

An additional operation can include adding the ranking score for thereference cell device and another ranking score determined for the celldevice proximate with the reference cell device to determine a referencebase station device ranking score, wherein a reference base stationdevice broadcast area includes or comprises or comprises a broadcastarea of the reference cell device and the cell device proximate to thereference cell device.

In accordance with this aspect, the reference base station deviceranking score can be color coded to indicate a comparative orderingbetween the reference base station device and another base stationdevice included in the network topology data, and the ranking score forthe reference cell device can be color coded to indicate a comparativeordering between the reference cell device and the cell device inproximity to the reference cell device. Further, the current performancevalue can be related to a defined quantity of data passing through thereference cell device during a defined unit of time, and the historicalperformance value is offered load data related to an available capacityon the reference cell device.

With reference now to the Figures. FIG. 1 illustrates a system 100 forrestoring cell site and/or evolved Node B (eNodeB) station devices aftera scheduled and/or unscheduled outage. System 100 can efficiently and inreal time provide cell site and eNodeB station device restorationpriority ranking metrics, wherein the restoration priority rankingmetrics account for all relevant key performance indicator (KPI) factorsand assigns optimal weights to each cell site and/or eNodeB stationdevice to reflect the cell site and/or eNodeB station device importanceand/or priority for restoration of service during outages and/ordisaster recovery scenarios. By using the functionalities and/orfacilities provided by system 100, reductions in the costs associatedwith restoring and/or troubleshooting multiple access wirelesscommunication networks/infrastructures (e.g., radio access networks)through the provision of real time metrics can be attained. The realtime metrics can be utilized or employed by network operators toefficiently and expeditiously identify and repair cell sites and/oreNodeB station devices during outage situations, thereby minimizing thetime necessary to restore cell sites and/or eNodeB station devices andproviding wireless coverage to critical areas and improved customerexperience.

As illustrated in FIG. 1, system 100 can include restoration engine 102that can be coupled to processor 104, memory 106, and storage 108. Asdepicted, restoration engine 102 can be in communication with processor104 for facilitating operation of computer executable instructions andcomponents by restoration engine 102, memory 106 for storing data and/orthe computer executable instructions and components, and storage 108 forproviding longer-term storage of data and/or computer executableinstructions. Additionally, system 100 can also receive input 110 foruse, manipulation, and/or transformation by restoration engine 102 toproduce one or more useful, concrete, and tangible result and/ortransform one or more article to different states or things. Further,system 100 can also generate and output the useful, concrete, andtangible result and/or the transformed one or more articles produced byrestoration engine 102 as output 112.

Restoration engine 102 can receive as input 110 current and/orhistorical key performance indicator (KPI) values. Typically these keyperformance indicator values can include total voice erlangs (e.g., thenumber of simultaneous users connected to the multiple access wirelesscommunication network/infrastructure via a cell site and/or eNodeBstation device—provides an indication regarding traffic demand and/orthe number of simultaneous voice calls that are being serviced orsupported by a cell site or eNodeB station device in a defined period oftime), data traffic traversing through a cell site and/or eNodeB stationdevice, short message service (SMS) traffic using a cell site and/oreNodeB station device as a conduit for communication, carried andoffered loads on a cell site and/or eNodeB station device, and the like.Other data that can be utilized by restoration engine 102 can includenetwork topologies (or geographically relevant or specific portions ofthe multiple access wireless communication network) of the multipleaccess wireless communication network/infrastructure, and cellrelationship information such relationship information based on handoverstatistics (e.g., the number of transfers of wireless service from afirst cell site and/or eNodeB station device to a second cell siteand/or eNodeB station device). It should noted that the foregoing keyperformance indicator values, network topologies, and/or cellrelationship information, such as handover statistics can be retrievedfrom one or more storage facilities (e.g., storage 108) and/or local,centrally located, and/or remotely situated databases. In someembodiments of the subject disclosure the storage facilities andassociated data can be stored and/or co-located at a cell site and/oreNodeB station device. In other embodiments of the subject disclosure,requisite data can have been stored to storage component 108. In stillother embodiments of the subject disclosure, the necessary data (e.g.,key performance indicator values, network topologies, and cellrelationship information) can be retrieve and/or obtained from databasesmaintained in a network cloud infrastructure.

With respect to the handover statistics received as input 110 byrestoration engine 102, these statistics are typically measured thenumber of transfers of wireless service from a first cell device to asecond cell device and/or from a first eNodeB station to a second eNodeBstation. The handover statistics are typically retrieved from a databasewhere the handover statistics are stored for each cell device includedin the multiple access wireless communication networks/infrastructure.The handover statistics provide a handover relationship betweendifferent or disparate cells and/or eNodeB station devices in themultiple access wireless communication network/infrastructure. Forinstance and with reference to and as depicted in FIG. 5, reference cellsite A and its neighbors cells site 1, cell site 2, cell site 3, cellsite 4, cell site 5, and cell site 6. The handover statistics maintainedin the one or more databases can be graphically illustrated as ahistogram that illustrates from the perspective of a first cell site(e.g. reference cell site A) how many handovers have been facilitated orconducted by reference cell site A to each of its neighboring cell sites(e.g., cell site 1, cell site 2, cell site 3, cell site 4, cell site 5,and cell site 6). It should be appreciated that the histographicalrepresentation of the handover statistics between the reference cellsite and each respective neighboring cell sites is but one illustrativegraphical representation that can be utilized, and is illustrated inFIG. 6.

As will be understood by those of ordinary skill in the art, the timewindow and/or granularity associated with measurement of the various keyperformance indicator values can be set by the multiple access wirelesscommunication network/infrastructure operator/carrier. Since ageographically diverse multiple access wireless communication network isa dynamic system that typically remains in a state of flux, theoperator/carrier may wish to utilize a brief time window/horizon (e.g.,a second (or fractions thereof), a few minutes, a half hour, an hour, .. . ) over which to provide analysis. Alternatively or optionally, themultiple access wireless communication network/infrastructureoperator/carrier may wish to set the time window/horizon to capture anwider view of the operational history of the geographically diversemultiple access wireless communication network/infrastructure (e.g. overthe last month, three months, six months, nine months, etc.). Inrelation to granularity, this aspect can also be set by the multipleaccess wireless communication network/infrastructure provider/carrier,and typically pertains to the sampling rate for the acquisition of thekey performance indicator values persisted or stored in the database(e.g., storage 108). Illustrative sampling rates for the acquisition ofkey performance indicator values can include collecting respective keyperformance indicator values every second, every minute, every thirtyminutes, every forty five minutes, every hour, every 90 minutes, everysix hours, every twelve hours, and the like.

Restoration engine 102 having received as input 110 key performanceindicator values, network topologies, and/or cell site relationshipinformation can apply a generic filtering algorithm/process, such as, asimple moving average algorithm/process, a weighted moving averagealgorithm/process, an exponential moving average algorithm/process, andthe like, to filter the key performance indicator values. The genericfiltering algorithm/process should combine current key performanceindicator values with historical key performance indicator values withina specified or defined time window, defined time horizon, defined timeperiod, to produce a post processed value for the key performanceindicator metric denoted as (Filtered_KPI)_(j) for each reference cellj.

Using the handover statistics (e.g., the number of transfers of wirelesscommunications that have occurred in a defined period of time between areference cell site (or reference eNodeB station device) and each cellsite (or each eNodeB station device) that neighbors the reference cellsite (or eNodeB station device)) retrieved and/or obtained as input 110,restoration engine 102 can apply a similar generic filteringalgorithm/process (e.g., a simple moving average algorithm/process, aweighted moving average algorithm/process, an exponential moving averagealgorithm/process, etc.) to the received or obtained handover statisticsto produce a processed value for the handover statistics. The postprocessed handover metric for a reference cell site j can be denoted as(Filtered_HO)_(j).

Additionally, restoration engine 102 can construct a distance weightingfactor that weights the contributions from neighboring cell sites(and/or eNodeB station devices) based on a distance between a referencecell site j (and/or eNodeB station device) and each of its neighboringcell sites (and/or eNodeB station devices). The metric generated byrestoration engine 102 can be determined as follows: first, restorationengine 102, using a network topology received as input 110, candetermine the distance between a reference cell site j and each of itsneighboring cell sites as defined in the network topology. This set ofdistances can be denoted as D_(net) _(—) _(top). Next, restorationengine 102, using the earlier received handover statistics, for example,can identify the number of neighbor cell sites that have contributed toa percentage value (x %) of the total handovers that have occurred in adefined unit of time. Based on the percentage value of contributionprovided by neighboring cell sites with respect to the reference cellsite j and the earlier determined set of distances (e.g., D_(net) _(—)_(top)) restoration engine 102 can determine the distance from referencecell site j to each neighboring cell site that has contributed to thedefined percentage value (x %) of the total number of handovers. Thisset of distances can be denoted as D_(HO) _(—) _(stat). Using the set ofdistances D_(HO) _(—) _(stat), restoration engine 102 can construct aweighting function for the reference cell site j. The weighting functioncan be denoted as W_(j) and measures the cardinality of the set ofdistances D_(HO) _(—) _(stat).

Restoration engine 102 can thereafter determine a cell site rankingscore value for the reference cell site j as:Cell_Ranking_Score_(j)=(Filtered_KPI_(j)+Filtered_HO_(j))×W_(j).Restoration engine 102, using the defined cell ranking score, can alsodetermine the eNodeB station device ranking score value for a referenceeNodeB station device j as: eNodeB_Ranking_Score_(j)=Σ_(i=1) ^(N) ^(i)Cell_Ranking_Score_(i), where N_(i) is the number of cell sitescontrolled by reference eNodeB station device j. As has been notedabove, restoration engine 102 (and system 100) provides both the cellsite ranking score value as well as the eNodeB station device rankingscore value in real time.

Using the determined cell site ranking score value as well as the eNodeBstation device ranking score value, restoration engine 102 inconjunction with a graphical user interface (GUI) can color code therespective cell site ranking score and eNodeB ranking score to provideoperations personnel a better perspective as to the priority orpreference ordering in which respective cell sites and/or eNodeB stationdevices should be restored. For instance, high priority cell sitesand/or eNodeB station devices (e.g., those cell sites and/or eNodeBstation devices that are critical or crucial for network operationswithin a defined geographical area) can be represented in red, while lowpriority cell sites and/or eNodeB station devices can be represented ina more neutral color, such as white. It should be appreciated in regardto display of the color coded ordering or ranking that other colorcombinations and/or color gradations can be utilized without departingfrom the intent and scope of the subject disclosure.

FIG. 2 provides further illustration of system 100 in accordance with anaspect of the subject disclosure. As illustrated system 100 can includerestoration engine 102 that can, as described above, be communicativelycoupled to processor 104, memory 106, and storage 108. Additionallysystem 100 can include preprocessing component 202 that can be incommunication with restoration engine 102 and can operate in conjunctionwith restoration engine 102. Preprocessing component 202 can receive, asinput 110, current and/or historical key performance indicator values,such as total voice erlangs, data traffic metrics, short message service(SMS) traffic metrics, carried and/or offered load metrics on aparticular cell site, for example. As has been noted above, currentand/or historical key performance indicator values can be retrievedand/or obtained from one or more databases that can be local to system100 and/or can be located in some central location geographicallydistant from system 100. Further, preprocessing component 202 can alsoreceive, as input 110, handover statistics—the total number of wirelesshandovers that can have occurred in a defined time window or time periodbetween a reference cell site j and each cell site that is proximate orneighbors reference cell site j.

Preprocessing component 202 on receipt of current and/or historical keyperformance indicator values can filter these values using a genericfiltering algorithm/process. Examples of such filteringalgorithms/processes can include a simple moving averagealgorithm/process, a cumulative moving average algorithm/process, aweighted moving average algorithm/process, an exponential weightedmoving average algorithm/process, and the like. These genericalgorithms/processes can be utilized by preprocessing component 202 tocombine current and/or historical key performance indicator informationwithin a defined or specified time window to produce a post processedvalue for the key performance indicator metric. This metric can bedenoted as (Filtered_KPI)_(j) for a particular cell site or referencecell site j.

Preprocessing component 202 can also on receipt, as input 110, ofhandover information and/or statistics can apply a similar genericfiltering algorithm/process to the received handover information and/orstatistics to produce a post processed handover metric. The receivedhandover statistics and/or information can include the total number ofhandovers that have occurred in a defined time window between areference cell site j and each of its neighboring cell sites, whereinthis information and/or these statistics are filtered and weighted usingthe generic filtering algorithm/process (e.g., one or more of a simplemoving average algorithm/process, a cumulative moving averagealgorithm/process, a weighted moving average algorithm/process, anexponential weighted moving average algorithm/process, and the like).The filtering and weighting of the handover information and/orstatistics produces a post processed handover metric for a particularreference cell site j can be denoted as (Filtered_HO)_(j).

Preprocessing component 1202 can thereafter supply or forward thedetermined metrics (e.g., Filtered_KPI_(j) and/or Filtered_H0_(j)) toranking component 302 for further processing as described in FIG. 3.

FIG. 3 provides additional illustration of system 100 in accordance witha further aspect of the subject disclosure. As illustrated, system 100can include ranking component 302 that can operate in collaboration orconjunction with restoration engine 102 which in turn can be incommunication with processor 104, memory 106, and/or storage 108.Ranking component 302 using one or more geographically relevant networktopology received as input 110 from one or more databases maintained,for example, by a multiple access wireless communicationnetwork/infrastructure provider/carrier can construct a distanceweighting factor that weights the contributions from neighboring cellsites based on, or as a function of, the distances between a referencecell site j and each cell site that neighbors reference cell site j.This metric can be determined as follows: initially, ranking component302, using the geographically relevant network topology informationreceived as input 110, can determine a distance between a reference cellsite j and each of its neighboring cell sites as defined in thegeographically relevant network topology. This set of distances can bedenoted as D_(net) _(—) _(top). Subsequently, using the handoverstatistics and/or handover relationship information, also received asinput 110, ranking component 302 can identify, from the perspective of areference cell site j, the number of neighboring cell sites that havecontributed to a percentage value (x %) of the total handovers that haveoccurred between the reference cell site j and cell sites in proximityof reference cell site j within a defined time window. Based on, or as afunction of, the number of neighboring cell sites that have contributedto a percentage value (x %) of the total handovers that have occurredbetween the reference cell site j and cell sites in proximity toreference cell site j and the set of distances D_(net) _(—) _(top),ranking component 302 can determine the distances from the referencecell site (e.g., reference cell site j) to each and every cell site thathas contributed to the percentage value (x %) of the total handoversthat have occurred between the reference cell site j and cell sitesproximate to the reference cell site j. This further set of distancesthat can be denoted as D_(HO) _(—) _(stat), can be used to construct aweighting function for the reference cell site j. The weighting functioncan be denoted as W_(j). The weighting function W_(j) measures thecardinality of the further set of distances D_(HO) _(—) _(stat).

Ranking component 302 can thereafter utilize the ascertained ordetermined post processed value for the key performance indicator metric(e.g. (Filtered_KPI)_(j) determined for each reference cell site j), thedetermined or ascertained post processed value for the handover metricfor reference cell site j (e.g., (Filtered_HO)_(j)), and the weightingfunction W_(j) that measures the cardinality of the further set ofdistances (e.g., D_(HO) _(—) _(stat)) to determine a cell site rankingscore value for a reference cell site j (e.g.,Cell_Ranking_Score_(j)=(Filtered_KPI_(j)+Filtered_HO_(j))×W_(j)).Additionally, ranking component 302, using the determinedCell_Ranking_Score, can also determine the eNodeB station device rankingscore for a particular reference eNodeB station device. The eNodeBstation device ranking score can be determined as:eNodeB_Ranking_Score_(j)=ΣN_(i=1) ^(N) ^(i) Cell_Ranking_Score_(i),where N_(i) is the number of cell sites controlled by reference eNodeBstation device j. The resultant cell site ranking score value (e.g.,Cell_Ranking_Score) and the eNodeB station device ranking score (e.g.,eNodeB_Ranking_Score) can thereafter be conveyed and processed byinterface component 402, as described below in FIG. 4.

FIG. 4 provides further illustration of system 100 in accordance withanother aspect of the subject disclosure. As illustrated, system 100 caninclude interface component 402 that can operate in collaboration withrestoration engine 102. As has been noted above, and as depicted in FIG.4 interface component 402 can be communicatively coupled to restorationengine 102 which in turn can be communicatively coupled to processor104, memory 106, and storage 108. Interface component 402 can receivethe resultant cell site ranking score value (e.g., Cell_Ranking_Score)and the eNodeB station device ranking score (e.g., eNodeB_Ranking_Score)generated by ranking component 302 and thereafter produce color codedoutput in relation to the cell site ranking score value and the eNodeBstation device ranking score. In accordance with an embodiment,interface component 402 can generate and display cell sites with highcell site ranking score values in the color red, thereby denoting thefact the such cell sites are of crucial importance and thus should berestored in priority to other cell sites with lower cell sites withcommensurately lower cell site ranking score values. Interface component402 can perform similar operations in connection with the eNodeB stationdevice ranking score, wherein interface component 402 can generate andcause a display device to display a tabulated representation of a colorcoded ranking or ordering of eNodeB station devices, prioritizing thoseeNodeB station devices that should be restored in preference to othereNodeB stations that can await restoration at a subsequent time.

FIG. 5 depicts an illustrative wireless cellular structure 500comprising a reference cell site A and its proximate or neighboring cellsites enumerated as cell site 1, cell site 2, cell site 3, cell site 4,cell site 5, and cell site 6. From the illustrative cellular structure500, system 100 can determine the respective distances between referencecell site A and each of cell site 1, cell site 2, cell site 3, cell site4, cell site 5, and cell site 6. Additionally, system 100 can determinehandover relationship information between reference cell site A and eachof neighboring cell site 1, cell site 2, cell site 3, cell site 4, cellsite 5, and cell site 6. The handover relationship information can berepresented as a histogram as depicted in FIG. 6.

FIG. 6 depicts an illustrative histogram 600 representative of thenumber of wireless handovers that have occurred between a reference cellsite (e.g., cell site A as illustrated in FIG. 5) and each cell sitethat is proximate or neighbors the reference cell site (e.g., cell site1, cell site 2, cell site 3, cell site 4, cell site 5, and cell site 6,as depicted in FIG. 5) within a defined time horizon or defined timewindow. As will be observed in this instance, the preponderance ofwireless handovers that have occurred between a reference cell site andeach of its respective neighbors have occurred between the referencecell site and cell site 5, whereas the least number of wirelesshandovers have been between the reference cell site and cell site 6.

FIG. 7 illustrates contiguous cell sites 700. In this depiction,contiguous cell sites 700 can include cell sites A1-A6, cell sitesB1-B6, and cell sites C1-C6, wherein each of cell sites A1-A6, cellsites B1-B6, and cell sites C1-C6 can be under control of individual andrespective eNodeB station devices. In this illustration, through thefacilities and functionalities provided by system 100, should adisruption occur with respect to cell sites A1-A6, cell sites B1-B6, andcell sites C1-C6, system 100 may determine, as a function of aCell_Ranking_Score and/or a eNodeB_Ranking_Score generated by system100, that in order to orderly restore wireless service to the entiretyof the coverage area of the three cell sites (e.g., cell sites A1-A6,cell sites B1-B6, and cell sites C1-C6), it might be beneficial toprioritize restoration of cell sites A1 and A5, since these cell sitescan also be utilized to service coverage areas that prior to the outagewere covered by cell sites B2 and C4 respectively.

In view of the example system(s) described above, example method(s) thatcan be implemented in accordance with the disclosed subject matter canbe better appreciated with reference to flowcharts in FIGS. 8-9. Forpurposes of simplicity of explanation, example methods disclosed hereinare presented and described as a series of acts; however, it is to beunderstood and appreciated that the claimed subject matter is notlimited by the order of acts, as some acts may occur in different ordersand/or concurrently with other acts from that shown and describedherein. For example, one or more example methods disclosed herein couldalternatively be represented as a series of interrelated states orevents, such as in a state diagram. Moreover, interaction diagram(s) mayrepresent methods in accordance with the disclosed subject matter whendisparate entities enact disparate portions of the methods. Furthermore,not all illustrated acts may be required to implement a describedexample method in accordance with the subject specification. Furtheryet, two or more of the disclosed example methods can be implemented incombination with each other, to accomplish one or more aspects hereindescribed. It should be further appreciated that the example methodsdisclosed throughout the subject specification are capable of beingstored on an article of manufacture (e.g., a computer-readable medium)to allow transporting and transferring such methods to computers forexecution, and thus implementation, by a processor or for storage in amemory.

FIG. 8 illustrates a method 800 for restoring cell sites and/or eNodeBstation devices after a scheduled and/or unscheduled wirelesscommunication outage. Method 800 can commence at 802 where currentand/or historical key performance indicator values can be processed orfiltered using a generic filtering algorithm/process, such as a weightedmoving average algorithm/process, an exponential weighted moving averagealgorithm/process, and the like. The generic filtering algorithm/processcan combine the current and/or historical key performance indicatorvalues over a defined time period to produce a post processed value forthe key performance indicator metric that can be denoted as(Filtered_KPI) for each cell site. At 804 handover information and/orstatistics can be processed, wherein a generic filteringalgorithm/process similar to that utilized to filter the current and/orhistorical key performance indicator values can be applied to thehandover information and/or statistics. The results of the applicationof the generic filtering algorithm/process to the handover informationand/or statistics can be a post processed handover metric denoted as(Filtered_HO) for each cell site that is included in the handoverinformation and/or statistics. At 806, weighting factors can begenerated. The weighting factors can be generated by utilizing one ormore geographically relevant network topology and constructing adistance weighting factor that weights the contributions fromneighboring cell sites based on, or as a function of, the distancebetween a reference cell site and each of its neighbors. This metric canbe determined as follows: using the one or more geographically relevantnetwork topology information obtained for example from a databasetypically maintained by a multiple access wireless communication networkprovider/carrier, a distance between a reference cell site and each ofits neighboring cell sites defined in the network topology can bedetermined. This set of distances can be denoted as D_(net) _(—) _(top).Next, using the handover statistics, also maintained in one or moredatabases typically maintained by the multiple access wirelesscommunication network provider/carrier, the number of neighbor cellsites that have contributed to a percentage value (x %) of the totalhandovers that have occurred during a defined period of time can beidentified. Based on, or as a function of, the handover statistics andthe set of distances between the reference cell site and each of itsneighboring cell sites, a respective distance from the reference cellsite and to each of the neighboring cell sites that have contributed toa percentage value (x %) of the total handovers can be determined. Thisset of distances can be denoted as D_(HO) _(—) _(stat). Using this setof distances (e.g., D_(HO) _(—) _(stat)), a weighting function for thereference cell site can be constructed. This weighting function can bedenoted as W_(j) for reference cell site j. The weighting function W_(j)measures the cardinality of the set of distances D_(HO) _(—) _(stat).

At 808 a cell site ranking score for the reference cell site j can becreated. The cell site ranking score value can be represented as:Cell_Ranking_Score_(j)=(Filtered_KPI_(j)+Filtered_HO_(j))×W_(j). At 810as function of the cell site ranking score an eNodeB station deviceranking score can also be generated or constructed. The eNodeB stationdevice ranking score can be represented as:eNodeB_Ranking_Score_(j)=Σ_(i=1) ^(N) ^(i) Cell_Ranking_Score_(i), whereN_(i) is the number of cell sites controlled by reference eNodeB stationdevice j. The cell site ranking score and the eNodeB station deviceranking score can thereafter be output and utilized by a graphical userinterface to represent in table form, for instance, the relativeimportance of the reference cell site and/or the reference eNodeBstation device.

FIG. 9 illustrates a further method 900 for restoring cell sites and/oreNodeB station devices after a scheduled and/or unscheduled wirelesscommunication outage. Method 900 can begin at 902, where a weightingfactor W_(j) for a reference cell site can be determined, by using oneor more geographically relevant network topologies and determiningdistances between a reference cell site j and each of its neighboringcell sites. This set of distances can be denoted as D_(net) _(—) _(top).At 904, using handover statistics and/or other handover relationshipinformation a determination can be made regarding the number ofneighboring cell sites that have contributed to a defined percentagevalue (x %) of the total handover that have occurred between thereference cell site j and each of its neighboring cell sites. At 906, asa function of, or based at least in part on, the set of distancesdenoted as D_(net) _(—) _(top) and the number of neighboring cell sitesthat have contributed to a defined percentage value (x %) of the totalnumber of handovers that have occurred between the reference cell site jand each cell site that is in proximity or neighbors reference cell sitej, a further set of distances can be generated; this further set ofdistances can be denoted as D_(HO) _(—) _(stat). Using the further setof distances (e.g., D_(HO) _(—) _(stat)) a weighting function W_(j) canbe produced. The weighting function W_(j) measures the cardinality(e.g., the number of elements included in the set) of the further set ofdistances D_(HO) _(—) _(stat).

FIG. 10 presents an example embodiment 1000 of a mobile network platform1010 that can implement and exploit one or more aspects of the disclosedsubject matter described herein. Generally, wireless network platform1010 can include components, e.g., nodes, gateways, interfaces, servers,or disparate platforms, that facilitate both packet-switched (PS) (e.g.,internet protocol (IP), frame relay, asynchronous transfer mode (ATM))and circuit-switched (CS) traffic (e.g., voice and data), as well ascontrol generation for networked wireless telecommunication. As anon-limiting example, wireless network platform 1010 can be included intelecommunications carrier networks, and can be considered carrier-sidecomponents as discussed elsewhere herein. Mobile network platform 1010includes CS gateway node(s) 1012 which can interface CS traffic receivedfrom legacy networks like telephony network(s) 1040 (e.g., publicswitched telephone network (PSTN), or public land mobile network (PLMN))or a signaling system #7 (SS7) network 1070. Circuit switched gatewaynode(s) 1012 can authorize and authenticate traffic (e.g., voice)arising from such networks. Additionally, CS gateway node(s) 1012 canaccess mobility, or roaming, data generated through SS7 network 1070;for instance, mobility data stored in a visited location register (VLR),which can reside in memory 1030. Moreover, CS gateway node(s) 1012interfaces CS-based traffic and signaling and PS gateway node(s) 1018.As an example, in a 3GPP UMTS network, CS gateway node(s) 1012 can berealized at least in part in gateway GPRS support node(s) (GGSN). Itshould be appreciated that functionality and specific operation of CSgateway node(s) 1012, PS gateway node(s) 1018, and serving node(s) 1016,is provided and dictated by radio technology(ies) utilized by mobilenetwork platform 1010 for telecommunication.

In addition to receiving and processing CS-switched traffic andsignaling, PS gateway node(s) 1018 can authorize and authenticatePS-based data sessions with served mobile devices. Data sessions caninclude traffic, or content(s), exchanged with networks external to thewireless network platform 1010, like wide area network(s) (WANs) 1050,enterprise network(s) 1070, and service network(s) 1080, which can beembodied in local area network(s) (LANs), can also be interfaced withmobile network platform 1010 through PS gateway node(s) 1018. It is tobe noted that WANs 1050 and enterprise network(s) 1060 can embody, atleast in part, a service network(s) like IP multimedia subsystem (IMS).Based on radio technology layer(s) available in technology resource(s)1017, packet-switched gateway node(s) 1018 can generate packet dataprotocol contexts when a data session is established; other datastructures that facilitate routing of packetized data also can begenerated. To that end, in an aspect, PS gateway node(s) 1018 caninclude a tunnel interface (e.g., tunnel termination gateway (TTG) in3GPP UMTS network(s) (not shown)) which can facilitate packetizedcommunication with disparate wireless network(s), such as Wi-Finetworks.

In embodiment 1000, wireless network platform 1010 also includes servingnode(s) 1016 that, based upon available radio technology layer(s) withintechnology resource(s) 1017, convey the various packetized flows of datastreams received through PS gateway node(s) 1018. It is to be noted thatfor technology resource(s) 1017 that rely primarily on CS communication,server node(s) can deliver traffic without reliance on PS gatewaynode(s) 1018; for example, server node(s) can embody at least in part amobile switching center. As an example, in a 3GPP UMTS network, servingnode(s) 1016 can be embodied in serving GPRS support node(s) (SGSN).

For radio technologies that exploit packetized communication, server(s)1014 in wireless network platform 1010 can execute numerous applicationsthat can generate multiple disparate packetized data streams or flows,and manage (e.g., schedule, queue, format . . . ) such flows. Suchapplication(s) can include add-on features to standard services (forexample, provisioning, billing, customer support . . . ) provided bywireless network platform 1010. Data streams (e.g., content(s) that arepart of a voice call or data session) can be conveyed to PS gatewaynode(s) 1018 for authorization/authentication and initiation of a datasession, and to serving node(s) 1016 for communication thereafter. Inaddition to application server, server(s) 1014 can include utilityserver(s), a utility server can include a provisioning server, anoperations and maintenance server, a security server that can implementat least in part a certificate authority and firewalls as well as othersecurity mechanisms, and the like. In an aspect, security server(s)secure communication served through wireless network platform 1010 toensure network's operation and data integrity in addition toauthorization and authentication procedures that CS gateway node(s) 1012and PS gateway node(s) 1018 can enact. Moreover, provisioning server(s)can provision services from external network(s) like networks operatedby a disparate service provider; for instance, WAN 1050 or GlobalPositioning System (GPS) network(s) (not shown). Provisioning server(s)can also provision coverage through networks associated to wirelessnetwork platform 1010 (e.g., deployed and operated by the same serviceprovider), such as femto-cell network(s) (not shown) that enhancewireless service coverage within indoor confined spaces and offloadradio access network resources in order to enhance subscriber serviceexperience within a home or business environment by way of UE 1075.

It is to be noted that server(s) 1014 can include one or more processorsconfigured to confer at least in part the functionality of macro networkplatform 1010. To that end, the one or more processor can execute codeinstructions stored in memory 1030, for example. It is should beappreciated that server(s) 1014 can include a content manager 1015,which operates in substantially the same manner as describedhereinbefore.

In example embodiment 1000, memory 1030 can store information related tooperation of wireless network platform 1010. Other operationalinformation can include provisioning information of mobile devicesserved through wireless platform network 1010, subscriber databases;application intelligence, pricing schemes, e.g., promotional rates,flat-rate programs, couponing campaigns; technical specification(s)consistent with telecommunication protocols for operation of disparateradio, or wireless, technology layers; and so forth. Memory 1030 canalso store information from at least one of telephony network(s) 1040,WAN 1050, enterprise network(s) 1060, or SS7 network 1070. In an aspect,memory 1030 can be, for example, accessed as part of a data storecomponent or as a remotely connected memory store.

In order to provide a context for the various aspects of the disclosedsubject matter, FIG. 11, and the following discussion, are intended toprovide a brief, general description of a suitable environment in whichthe various aspects of the disclosed subject matter can be implemented.While the subject matter has been described above in the general contextof computer-executable instructions of a computer program that runs on acomputer and/or computers, those skilled in the art will recognize thatthe disclosed subject matter also can be implemented in combination withother program modules. Generally, program modules include routines,programs, components, data structures, etc. that perform particulartasks and/or implement particular abstract data types.

In the subject specification, terms such as “store,” “storage,” “datastore,” data storage,” “database,” and substantially any otherinformation storage component relevant to operation and functionality ofa component, refer to “memory components,” or entities embodied in a“memory” or components comprising the memory. It will be appreciatedthat the memory components described herein can be either volatilememory or nonvolatile memory, or can include both volatile andnonvolatile memory, by way of illustration, and not limitation, volatilememory 1120 (see below), non-volatile memory 1122 (see below), diskstorage 1124 (see below), and memory storage 1146 (see below). Further,nonvolatile memory can be included in read only memory (ROM),programmable ROM (PROM), electrically programmable ROM (EPROM),electrically erasable ROM (EEPROM), or flash memory. Volatile memory caninclude random access memory (RAM), which acts as external cache memory.By way of illustration and not limitation, RAM is available in manyforms such as synchronous RAM (SRAM), dynamic RAM (DRAM), synchronousDRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM(ESDRAM), Synchlink DRAM (SLDRAM), and direct Rambus RAM (DRRAM).Additionally, the disclosed memory components of systems or methodsherein are intended to comprise, without being limited to comprising,these and any other suitable types of memory.

Moreover, it will be noted that the disclosed subject matter can bepracticed with other computer system configurations, includingsingle-processor or multiprocessor computer systems, mini-computingdevices, mainframe computers, as well as personal computers, hand-heldcomputing devices (e.g., PDA, phone, watch, tablet computers, netbookcomputers, . . . ), microprocessor-based or programmable consumer orindustrial electronics, and the like. The illustrated aspects can alsobe practiced in distributed computing environments where tasks areperformed by remote processing devices that are linked through acommunications network; however, some if not all aspects of the subjectdisclosure can be practiced on stand-alone computers. In a distributedcomputing environment, program modules can be located in both local andremote memory storage devices.

FIG. 11 illustrates a block diagram of a computing system 1100 operableto execute the disclosed systems and methods in accordance with anembodiment. Computer 1112, which can be, for example, part of thehardware of system 100, includes a processing unit 1114, a system memory1116, and a system bus 1118. System bus 1118 couples system componentsincluding, but not limited to, system memory 1116 to processing unit1114. Processing unit 1114 can be any of various available processors.Dual microprocessors and other multiprocessor architectures also can beemployed as processing unit 1114.

System bus 1118 can be any of several types of bus structure(s)including a memory bus or a memory controller, a peripheral bus or anexternal bus, and/or a local bus using any variety of available busarchitectures including, but not limited to, Industrial StandardArchitecture (ISA), Micro-Channel Architecture (MSA), Extended ISA(EISA), Intelligent Drive Electronics, VESA Local Bus (VLB), PeripheralComponent Interconnect (PCI), Card Bus, Universal Serial Bus (USB),Advanced Graphics Port (AGP), Personal Computer Memory CardInternational Association bus (PCMCIA), Firewire (IEEE 1194), and SmallComputer Systems Interface (SCSI).

System memory 1116 can include volatile memory 1120 and nonvolatilememory 1122. A basic input/output system (BIOS), containing routines totransfer information between elements within computer 1112, such asduring start-up, can be stored in nonvolatile memory 1122. By way ofillustration, and not limitation, nonvolatile memory 1122 can includeROM, PROM, EPROM, EEPROM, or flash memory. Volatile memory 1120 includesRAM, which acts as external cache memory. By way of illustration and notlimitation, RAM is available in many forms such as SRAM, dynamic RAM(DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM),enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), Rambus direct RAM(RDRAM), direct Rambus dynamic RAM (DRDRAM), and Rambus dynamic RAM(RDRAM).

Computer 1112 can also include removable/non-removable,volatile/non-volatile computer storage media. FIG. 11 illustrates, forexample, disk storage 1124. Disk storage 1124 includes, but is notlimited to, devices like a magnetic disk drive, floppy disk drive, tapedrive, flash memory card, or memory stick. In addition, disk storage1124 can include storage media separately or in combination with otherstorage media including, but not limited to, an optical disk drive suchas a compact disk ROM device (CD-ROM), CD recordable drive (CD-R Drive),CD rewritable drive (CD-RW Drive) or a digital versatile disk ROM drive(DVD-ROM). To facilitate connection of the disk storage devices 1124 tosystem bus 1118, a removable or non-removable interface is typicallyused, such as interface 1126.

Computing devices typically include a variety of media, which caninclude computer-readable storage media or communications media, whichtwo terms are used herein differently from one another as follows.

Computer-readable storage media can be any available storage media thatcan be accessed by the computer and includes both volatile andnonvolatile media, removable and non-removable media. By way of example,and not limitation, computer-readable storage media can be implementedin connection with any method or technology for storage of informationsuch as computer-readable instructions, program modules, structureddata, or unstructured data. Computer-readable storage media can include,but are not limited to, RAM, ROM, EEPROM, flash memory or other memorytechnology, CD-ROM, digital versatile disk (DVD) or other optical diskstorage, magnetic cassettes, magnetic tape, magnetic disk storage orother magnetic storage devices, or other tangible media which can beused to store desired information. In this regard, the term “tangible”herein as may be applied to storage, memory or computer-readable media,is to be understood to exclude only propagating intangible signals perse as a modifier and does not relinquish coverage of all standardstorage, memory or computer-readable media that are not only propagatingintangible signals per se. In an aspect, tangible media can includenon-transitory media wherein the term “non-transitory” herein as may beapplied to storage, memory or computer-readable media, is to beunderstood to exclude only propagating transitory signals per se as amodifier and does not relinquish coverage of all standard storage,memory or computer-readable media that are not only propagatingtransitory signals per se. For the avoidance of doubt, the term“computer-readable storage device” is used and defined herein to excludetransitory media. Computer-readable storage media can be accessed by oneor more local or remote computing devices, e.g., via access requests,queries or other data retrieval protocols, for a variety of operationswith respect to the information stored by the medium.

Communications media typically embody computer-readable instructions,data structures, program modules or other structured or unstructureddata in a data signal such as a modulated data signal, e.g., a carrierwave or other transport mechanism, and includes any information deliveryor transport media. The term “modulated data signal” or signals refersto a signal that has one or more of its characteristics set or changedin such a manner as to encode information in one or more signals. By wayof example, and not limitation, communication media include wired media,such as a wired network or direct-wired connection, and wireless mediasuch as acoustic, RF, infrared and other wireless media.

It can be noted that FIG. 11 describes software that acts as anintermediary between users and computer resources described in suitableoperating environment 1100. Such software includes an operating system1128. Operating system 1128, which can be stored on disk storage 1124,acts to control and allocate resources of computer system 1112. Systemapplications 1130 take advantage of the management of resources byoperating system 1128 through program modules 1132 and program data 1134stored either in system memory 1116 or on disk storage 1124. It is to benoted that the disclosed subject matter can be implemented with variousoperating systems or combinations of operating systems.

A user can enter commands or information into computer 1112 throughinput device(s) 1136. As an example, system 100 can include a userinterface embodied in a touch sensitive display panel allowing a user tointeract with computer 1112. Input devices 1136 include, but are notlimited to, a pointing device such as a mouse, trackball, stylus, touchpad, keyboard, microphone, joystick, game pad, satellite dish, scanner,TV tuner card, digital camera, digital video camera, web camera, cellphone, smartphone, tablet computer, etc. These and other input devicesconnect to processing unit 1114 through system bus 1118 by way ofinterface port(s) 1138. Interface port(s) 1138 include, for example, aserial port, a parallel port, a game port, a universal serial bus (USB),an infrared port, a Bluetooth port, an IP port, or a logical portassociated with a wireless service, etc. Output device(s) 1140 use someof the same type of ports as input device(s) 1136.

Thus, for example, a USB port can be used to provide input to computer1112 and to output information from computer 1112 to an output device1140. Output adapter 1142 is provided to illustrate that there are someoutput devices 1140 like monitors, speakers, and printers, among otheroutput devices 1140, which use special adapters. Output adapters 1142include, by way of illustration and not limitation, video and soundcards that provide means of connection between output device 1140 andsystem bus 1118. It should be noted that other devices and/or systems ofdevices provide both input and output capabilities such as remotecomputer(s) 1144.

Computer 1112 can operate in a networked environment using logicalconnections to one or more remote computers, such as remote computer(s)1144. Remote computer(s) 1144 can be a personal computer, a server, arouter, a network PC, cloud storage, cloud service, a workstation, amicroprocessor based appliance, a peer device, or other common networknode and the like, and typically includes many or all of the elementsdescribed relative to computer 1112.

For purposes of brevity, only a memory storage device 1146 isillustrated with remote computer(s) 1144. Remote computer(s) 1144 islogically connected to computer 1112 through a network interface 1148and then physically connected by way of communication connection 1150.Network interface 1148 encompasses wire and/or wireless communicationnetworks such as local-area networks (LAN) and wide-area networks (WAN).LAN technologies include Fiber Distributed Data Interface (FDDI), CopperDistributed Data Interface (CDDI), Ethernet, Token Ring and the like.WAN technologies include, but are not limited to, point-to-point links,circuit-switching networks like Integrated Services Digital Networks(ISDN) and variations thereon, packet switching networks, and DigitalSubscriber Lines (DSL). As noted below, wireless technologies may beused in addition to or in place of the foregoing.

Communication connection(s) 1150 refer(s) to hardware/software employedto connect network interface 1148 to bus 1118. While communicationconnection 1150 is shown for illustrative clarity inside computer 1112,it can also be external to computer 1112. The hardware/software forconnection to network interface 1148 can include, for example, internaland external technologies such as modems, including regular telephonegrade modems, cable modems and DSL modems, ISDN adapters, and Ethernetcards.

The above description of illustrated embodiments of the subjectdisclosure, including what is described in the Abstract, is not intendedto be exhaustive or to limit the disclosed embodiments to the preciseforms disclosed. While specific embodiments and examples are describedherein for illustrative purposes, various modifications are possiblethat are considered within the scope of such embodiments and examples,as those skilled in the relevant art can recognize.

In this regard, while the disclosed subject matter has been described inconnection with various embodiments and corresponding Figures, whereapplicable, it is to be understood that other similar embodiments can beused or modifications and additions can be made to the describedembodiments for performing the same, similar, alternative, or substitutefunction of the disclosed subject matter without deviating therefrom.Therefore, the disclosed subject matter should not be limited to anysingle embodiment described herein, but rather should be construed inbreadth and scope in accordance with the appended claims below.

As it employed in the subject specification, the term “processor” canrefer to substantially any computing processing unit or devicecomprising, but not limited to comprising, single-core processors;single-processors with software multithread execution capability;multi-core processors; multi-core processors with software multithreadexecution capability; multi-core processors with hardware multithreadtechnology; parallel platforms; and parallel platforms with distributedshared memory. Additionally, a processor can refer to an integratedcircuit, an application specific integrated circuit (ASIC), a digitalsignal processor (DSP), a field programmable gate array (FPGA), aprogrammable logic controller (PLC), a complex programmable logic device(CPLD), a discrete gate or transistor logic, discrete hardwarecomponents, or any combination thereof designed to perform the functionsdescribed herein. Processors can exploit nano-scale architectures suchas, but not limited to, molecular and quantum-dot based transistors,switches and gates, in order to optimize space usage or enhanceperformance of user equipment. A processor may also be implemented as acombination of computing processing units.

In the subject specification, terms such as “store,” “storage,” “datastore,” data storage,” “database,” and substantially any otherinformation storage component relevant to operation and functionality ofa component, refer to “memory components,” or entities embodied in a“memory” or components comprising the memory. It will be appreciatedthat the memory components described herein can be either volatilememory or nonvolatile memory, or can include both volatile andnonvolatile memory.

As used in this application, the terms “component,” “system,”“platform,” “layer,” “selector,” “interface,” and the like are intendedto refer to a computer-related entity or an entity related to anoperational apparatus with one or more specific functionalities, whereinthe entity can be either hardware, a combination of hardware andsoftware, software, or software in execution. As an example, a componentmay be, but is not limited to being, a process running on a processor, aprocessor, an object, an executable, a thread of execution, a program,and/or a computer. By way of illustration and not limitation, both anapplication running on a server and the server can be a component. Oneor more components may reside within a process and/or thread ofexecution and a component may be localized on one computer and/ordistributed between two or more computers. In addition, these componentscan execute from various computer readable media having various datastructures stored thereon. The components may communicate via localand/or remote processes such as in accordance with a signal having oneor more data packets (e.g., data from one component interacting withanother component in a local system, distributed system, and/or across anetwork such as the Internet with other systems via the signal). Asanother example, a component can be an apparatus with specificfunctionality provided by mechanical parts operated by electric orelectronic circuitry, which is operated by a software or firmwareapplication executed by a processor, wherein the processor can beinternal or external to the apparatus and executes at least a part ofthe software or firmware application. As yet another example, acomponent can be an apparatus that provides specific functionalitythrough electronic components without mechanical parts, the electroniccomponents can include a processor therein to execute software orfirmware that confers at least in part the functionality of theelectronic components.

In addition, the term “or” is intended to mean an inclusive “or” ratherthan an exclusive “or.” That is, unless specified otherwise, or clearfrom context, “X employs A or B” is intended to mean any of the naturalinclusive permutations. That is, if X employs A; X employs B; or Xemploys both A and B, then “X employs A or B” is satisfied under any ofthe foregoing instances. Moreover, articles “a” and “an” as used in thesubject specification and annexed drawings should generally be construedto mean “one or more” unless specified otherwise or clear from contextto be directed to a singular form.

Moreover, terms like “user equipment (UE),” “mobile station,” “mobile,”subscriber station,” “subscriber equipment,” “access terminal,”“terminal,” “handset,” and similar terminology, refer to a wirelessdevice utilized by a subscriber or user of a wireless communicationservice to receive or convey data, control, voice, video, sound, gaming,or substantially any data-stream or signaling-stream. The foregoingterms are utilized interchangeably in the subject specification andrelated drawings. Likewise, the terms “access point (AP),” “basestation,” “NodeB,” “evolved Node B (eNodeB),” “home Node B (HNB),” “homeaccess point (HAP),” “cell device,” “sector,” “cell,” and the like, areutilized interchangeably in the subject application, and refer to awireless network component or appliance that serves and receives data,control, voice, video, sound, gaming, or substantially any data-streamor signaling-stream to and from a set of subscriber stations or providerenabled devices. Data and signaling streams can include packetized orframe-based flows.

Additionally, the terms “core-network”, “core”, “core carrier network”,“carrier-side”, or similar terms can refer to components of atelecommunications network that typically provides some or all ofaggregation, authentication, call control and switching, charging,service invocation, or gateways. Aggregation can refer to the highestlevel of aggregation in a service provider network wherein the nextlevel in the hierarchy under the core nodes is the distribution networksand then the edge networks. UEs do not normally connect directly to thecore networks of a large service provider but can be routed to the coreby way of a switch or radio area network. Authentication can refer todeterminations regarding whether the user requesting a service from thetelecom network is authorized to do so within this network or not. Callcontrol and switching can refer determinations related to the futurecourse of a call stream across carrier equipment based on the callsignal processing. Charging can be related to the collation andprocessing of charging data generated by various network nodes. Twocommon types of charging mechanisms found in present day networks can beprepaid charging and postpaid charging. Service invocation can occurbased on some explicit action (e.g. call transfer) or implicitly (e.g.,call waiting). It is to be noted that service “execution” may or may notbe a core network functionality as third party network/nodes may takepart in actual service execution. A gateway can be present in the corenetwork to access other networks. Gateway functionality can be dependenton the type of the interface with another network.

Furthermore, the terms “user,” “subscriber,” “customer,” “consumer,”“prosumer,” “agent,” and the like are employed interchangeablythroughout the subject specification, unless context warrants particulardistinction(s) among the terms. It should be appreciated that such termscan refer to human entities or automated components (e.g., supportedthrough artificial intelligence, as through a capacity to makeinferences based on complex mathematical formalisms), that can providesimulated vision, sound recognition and so forth.

Aspects, features, or advantages of the subject matter can be exploitedin substantially any, or any, wired, broadcast, wirelesstelecommunication, radio technology or network, or combinations thereof.Non-limiting examples of such technologies or networks include Geocasttechnology; broadcast technologies (e.g., sub-Hz, ELF, VLF, LF, MF, HF,VHF, UHF, SHF, THz broadcasts, etc.); Ethernet; X.25; powerline-typenetworking (e.g., PowerLine AV Ethernet, etc.); femto-cell technology;Wi-Fi; Worldwide Interoperability for Microwave Access (WiMAX); EnhancedGeneral Packet Radio Service (Enhanced GPRS); Third GenerationPartnership Project (3GPP or 3G) Long Term Evolution (LTE); 3GPPUniversal Mobile Telecommunications System (UMTS) or 3GPP UMTS; ThirdGeneration Partnership Project 2 (3GPP2) Ultra Mobile Broadband (UMB);High Speed Packet Access (HSPA); High Speed Downlink Packet Access(HSDPA); High Speed Uplink Packet Access (HSUPA); GSM Enhanced DataRates for GSM Evolution (EDGE) Radio Access Network (RAN) or GERAN; UMTSTerrestrial Radio Access Network (UTRAN); or LTE Advanced.

What has been described above includes examples of systems and methodsillustrative of the disclosed subject matter. It is, of course, notpossible to describe every combination of components or methods herein.One of ordinary skill in the art may recognize that many furthercombinations and permutations of the claimed subject matter arepossible. Furthermore, to the extent that the terms “includes,” “has,”“possesses,” and the like are used in the detailed description, claims,appendices and drawings such terms are intended to be inclusive in amanner similar to the term “comprising” as “comprising” is interpretedwhen employed as a transitional word in a claim.

What is claimed is:
 1. A system, comprising: a memory to storeexecutable instructions; and a processor, coupled to the memory, thatfacilitates execution of the executable instructions to performoperations, comprising: receiving a current key performance indicatorvalue, topology data representing a network topology relating to a firstcell device, and statistical data representing a statistic related to anumber of transfers of wireless service from the first cell device to asecond cell device; filtering the current performance indicator valuefor the first cell device over a defined time period to produce afiltered key performance indicator metric for the first cell device;filtering the statistical data over the defined time period to producefiltered statistical data representing a filtered statistic for thefirst cell device of the number of transfers of wireless service fromthe first cell device to the second cell device; determining, as afunction of the topology data, a weighting factor for the first celldevice based on distance data representing a distance between the firstcell device and the second cell device and the number of transfers ofwireless service from the first cell device to the second cell device;and initiating display of a cell ranking score for the first cell deviceas a function of the weighting factor for the first cell device, thefiltered key performance indicator metric for the first cell device, andthe filtered statistical data for the first cell device.
 2. The systemof claim 1, wherein the operations further comprise receiving ahistorical key performance indicator value and filtering the historicalperformance indicator value for the first cell device and the currentkey performance indicator value for the first cell device over thedefined time period to produce the filtered key performance indicatorfor the first cell device.
 3. The system of claim 1, wherein theoperations further comprise aggregating the cell ranking score for celldevices included in a coverage area of a base station device to producea base station device ranking score for the base station device.
 4. Thesystem of claim 3, wherein the operations further comprise initiatingdisplay of the base station device ranking score.
 5. The system of claim3, wherein the first cell device and the second cell device are includedin the coverage area of the base station device, and the base stationdevice is included in the topology data.
 6. The system of claim 1,wherein the current key performance indicator value is a measure of acurrent load on the first cell device.
 7. The system of claim 1, whereinthe current key performance indicator value is a metric related to anumber of concurrent voice calls that are being serviced by the firstcell device during the defined time period.
 8. A method, comprising:obtaining, by a system comprising a processor, a historical keyperformance indicator value, topology data representing a networktopology, and statistical data representing a metric related to a numberof transfers of wireless service from a reference cell device to aneighboring cell device; applying a filtering process to the historicalperformance indicator value for the reference cell device to produce afiltered key performance indicator metric for the reference cell device;applying the filtering process to the statistical data for the referencecell device to produce a filtered handover metric related to the numberof transfers; determining a weighting factor for the reference celldevice using the topology data and the number of transfers, wherein thetopology data enables determination of a distance between the referencecell device and the neighboring cell device; and initiating display of acell ranking score for the reference cell device as a function of theweighting factor for the reference cell device, the filtered handovermetric for the reference cell device, and the filtered key performanceindicator metric for the reference cell device.
 9. The method of claim8, wherein the filtering process is a weighted moving average process.10. The method of claim 8, wherein the filtering process is anexponential weighted moving average process.
 11. The method of claim 8,further comprising, aggregating the cell ranking score for the referencecell device with a cell ranking score determined for the neighboringcell device to determine an eNodeB station device ranking score for areference eNodeB station device, wherein the reference eNodeB stationdevice comprises the reference cell device.
 12. The method of claim 11,further comprising, initiating display of the eNodeB station deviceranking score for the reference eNodeB station device, wherein theeNodeB station ranking score is color coded as a function of a priorityordering placed on restoration of the reference eNodeB station devicerelative to the neighboring cell device included in a geographic segmentof a multiple access wireless communication network represented by thetopology data.
 13. The method of claim 8, wherein the historical keyperformance indicator value is a metric related to a quantity of datatraffic passing through the reference cell device for a defined unit oftime.
 14. The method of claim 8, wherein the historical key performanceindicator value is a metric related to an amount of data related to atext message service using the reference cell device as a conduit forcommunication with a network device associated with a multiple accesswireless communication network.
 15. A computer readable storage devicecomprising executable instructions that, in response to execution, causea system comprising a processor to perform operations, comprising:filtering a current key performance indicator value for a reference celldevice and a historical key performance indicator value for thereference cell device to produce a filtered key performance indicatormetric for the reference cell device related to a defined time horizon;filtering statistical data to produce filtered statistical datarepresenting a filtered statistic for the reference cell device relatedto the defined time horizon; determining a weighting factor for thereference cell device as a function a distance between the referencecell device and a cell device in proximity to the reference cell device,wherein the distance is obtained from topology data representing anetwork topology that comprises the reference cell device and the celldevice in proximity to the reference cell device; and initiating displayof a ranking score for the reference cell device, wherein the rankingscore for the reference cell device is determined as a function of theweighting factor for the reference cell device, the filtered statisticaldata for the reference cell device, and the filtered key performanceindicator metric for the reference cell device.
 16. The computerreadable storage device of claim 15, wherein the ranking score for thereference cell device is color coded to indicate a comparative orderingbetween the reference cell device and the cell device in proximity tothe reference cell device.
 17. The computer readable storage device ofclaim 15, wherein the operations further comprise adding the rankingscore for the reference cell device and another ranking score determinedfor the cell device proximate with the reference cell device todetermine a reference base station device ranking score, wherein areference base station device broadcast area comprises a broadcast areaof the reference cell device and the cell device proximate to thereference cell device.
 18. The computer readable storage device of claim17, wherein the reference base station device ranking score is colorcoded to indicate a comparative ordering between the reference basestation device and another base station device included in the networktopology data.
 19. The computer readable storage device of claim 15,wherein the current performance value is related to a defined quantityof data passing through the reference cell device during the definedunit of time.
 20. The computer readable storage device of claim 15,wherein the historical performance value is offered load data related toan available capacity on the reference cell device.